Tag: resources

We’re building an artificial intelligence-powered dystopia, one click at a time, says techno-sociologist Zeynep Tufekci.

In an eye-opening talk, she details how the same algorithms companies like Facebook, Google and Amazon use to get you to click on ads are also used to organize your access to political and social information.

We’re building an artificial intelligence-powered dystopia, one click at a time, says techno-sociologist Zeynep Tufekci. In an eye-opening talk, she details how the same algorithms companies like Facebook, Google and Amazon use to get you to click on ads are also used to organize your access to political and social information. And the machines aren’t even the real threat. What we need to understand is how the powerful might use AI to control us — and what we can do in response. Continue reading “Zeynep Tufekci: We’re building a dystopia just to make people click on ads”

So, the question is, where are these vendors getting their training sets that make their AI useful to solve your data management problems?

In the world of data management, the best source of training sets comes from metadata.

All this data provides a wealth of information for AI/ML to make suggestions and recommendations that will boost productivity of users.

If you would like to cut short a vendor evaluation, here are some questions to ask the vendor claiming to have AI integrated with their data management solution: – – Just the first two or three questions should be enough to save you from an hour of “Death by PowerPoint.”…

And while many of the tech giants working on AI like Google and Facebook have open sourced some of their algorithms, they hold back most of their data.In contrast, blockchains represent and even incent open data.

For example: creating a decentralized Uber requires a relatively open dataset of riders and drivers available to coordinate the network.The network effects and economic incentives around these open systems and their data can be more powerful than current centralized companies because they are open standards that anyone can build on in the same way the protocols of the internet like TCP/IP, HTML, and SMTP have achieved far greater scale than any company that sits atop them.

And oracle systems (a fancy way of saying getting people all over the world to report real world information to the blockchain in a way we can trust) like Augur will inject more data.This open data has the potential to commoditize the data silos most tech companies like Google, Facebook, Uber, LinkedIn, and Amazon are built on and extract rent from.

AIs trained on open data are more likely to be neutral and trustworthy instead of biased by the interests of the corporation who created and trained them.Since blockchains allow us to explicitly program incentive structures, they may make the incentives of AI more transparent.Simplified, AI is driven by 3 things: tools, compute power, and training data.

My guess is they shift to 1) creating blockchain protocols and their native tokens and 2) AIs that leverage the open, global data layer of the blockchain.

” What Every Manager Should Know About Machine Learning ” by Mike Yeomans

Product managers need to understand the current state of AI, and the opportunities that machine learning and techniques such as deep learning provide for transforming your products and delighting your users.

Machine learning is changing the face of computing, and faster than many of us ever imagined.